Workshop on high performance data intensive computing

2016 ◽  
Vol 28 (6) ◽  
pp. 1695-1696
Author(s):  
Yunquan Zhang ◽  
Ji-Lin Zhang
Keyword(s):  
High Performance ◽  
Performance Data ◽  
Data Intensive Computing ◽  
Data Intensive

Hardware Technologies for High-Performance Data-Intensive Computing

Computer ◽  
2008 ◽  
Vol 41 (4) ◽  
pp. 60-68 ◽  
Author(s):  
Maya Gokhale ◽  
Jonathan Cohen ◽  
Andy Yoo ◽  
W. Marcus Miller ◽  
Arpith Jacob ◽  
...  
Keyword(s):  
High Performance ◽  
Performance Data ◽  
Data Intensive Computing ◽  
Data Intensive

scholarly journals Enabling Large-Scale Biomedical Analysis in the Cloud

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Ying-Chih Lin ◽  
Chin-Sheng Yu ◽  
Yen-Jen Lin
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Computing System ◽  
Biomedical Data ◽  
Data Intensive Computing ◽  
Biomedical Analysis ◽  
Data Intensive ◽  
Large Scale Data ◽  
Performance Computing ◽  
Scale Data

Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable.

Overview of Big Data-Intensive Storage and its Technologies for Cloud and Fog Computing

2021 ◽  
pp. 112-153
Author(s):  
Richard S. Segall ◽  
Jeffrey S Cook ◽  
Gao Niu
Keyword(s):  
Big Data ◽  
Data Storage ◽  
High Performance ◽  
Storage Systems ◽  
Fog Computing ◽  
Storage Management ◽  
Data Intensive Computing ◽  
Computing Systems ◽  
Application Performance ◽  
Data Intensive

Computing systems are becoming increasingly data-intensive because of the explosion of data and the needs for processing the data, and subsequently storage management is critical to application performance in such data-intensive computing systems. However, if existing resource management frameworks in these systems lack the support for storage management, this would cause unpredictable performance degradation when applications are under input/output (I/O) contention. Storage management of data-intensive systems is a challenge. Big Data plays a most major role in storage systems for data-intensive computing. This article deals with these difficulties along with discussion of High Performance Computing (HPC) systems, background for storage systems for data-intensive applications, storage patterns and storage mechanisms for Big Data, the Top 10 Cloud Storage Systems for data-intensive computing in today's world, and the interface between Big Data Intensive Storage and Cloud/Fog Computing. Big Data storage and its server statistics and usage distributions for the Top 500 Supercomputers in the world are also presented graphically and discussed as data-intensive storage components that can be interfaced with Fog-to-cloud interactions and enabling protocols.

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